Heterogeneous evolution of SARS-CoV-2 seroprevalence in school-age children: Results from the school-based cohort study Ciao Corona in November-December 2021 in the canton of Zurich
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Abstract
Background
Much remains unknown regarding the evolution of SARS-CoV-2 seroprevalence and variability in seropositive children in districts, schools, and classes as only a few school-based co-hort studies exist. Vaccination of children, initiated at different times for different age groups, adds additional complexity to understand how seroprevalence developed in the school aged population.
Aim
We investigated the evolution of SARS-CoV-2 seroprevalence in children and its variability in districts, schools, and classes in Switzerland from June/July 2020 to November/December 2021.
Methods
In this school-based cohort study, SARS-CoV-2 antibodies were measured in primary and secondary school children from randomly selected schools in the canton of Zurich in October/November 2020, March/April 2021, and November/December 2021. Seroprevalence was estimated using Bayesian logistic regression to adjust for test sensitivity and specificity. Variability of seroprevalence between school classes was expressed as maximum minus minimum sero-prevalence in a class and summarized as median (interquartile range).
Results
1875 children from 287 classes in 43 schools were tested, with median age 12 (range 6-17), 51% 12+ vaccinated. Seroprevalence increased from 5.6% (95% CrI: 3.5-7.6%) to 31.1% (27.0-36.1%) in unvaccinated children, and 46.4% (42.6-50.9%) in all children (including vaccinated). Earlier in the pandemic, seropositivity rates in primary schools were similar to or slightly higher (<5%) than those in secondary schools, but by late 2021, primary schools had 12.3% (44.3%) lower seroprevalence for unvaccinated (all) subjects. Variability in seroprevalence among districts and schools increased more than twofold over time, and in classes from 11% (7-17%) to 40% (22-49%).
Conclusion
Seroprevalence in children increased greatly, especially in 2021 following introduction of vaccines. Variability in seroprevalence was high and increased substantially over time, suggesting complex transmission chains.
Trial Registration: ClinicalTrials.gov NCT04448717
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SciScore for 10.1101/2022.05.31.22275814: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources 24 The test uses Luminex technology to detect IgG and IgA antibodies binding to the entire trimeric S protein of SARS-CoV-2 and with demonstrated 94.0% sensitivity and 99.2% specificity for testing of IgG. At T4, two different definitions of seroprevalence were considered: a) Seroprevalence in tested children without documented vaccination, or b) Seroprevalence in all tested children (including those reporting vaccination). IgAsuggested: NoneThe Bayesian approach allowed to account for the sensitivity and specificity of the SARS-CoV-2 antibody test and the hierarchical structure of cohort (individual … SciScore for 10.1101/2022.05.31.22275814: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources 24 The test uses Luminex technology to detect IgG and IgA antibodies binding to the entire trimeric S protein of SARS-CoV-2 and with demonstrated 94.0% sensitivity and 99.2% specificity for testing of IgG. At T4, two different definitions of seroprevalence were considered: a) Seroprevalence in tested children without documented vaccination, or b) Seroprevalence in all tested children (including those reporting vaccination). IgAsuggested: NoneThe Bayesian approach allowed to account for the sensitivity and specificity of the SARS-CoV-2 antibody test and the hierarchical structure of cohort (individual and school levels). SARS-CoV-2suggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This study also has limitations. Due to the nature of serological testing, exact timing of infections cannot be determined. Therefore, examination of associated infections, in the sense of outbreaks or temporal clusters of infections, is not possible. We used a highly accurate serological test and adjusted for inaccuracy using Bayesian models on a population level, but it is not possible to avoid some false positive or false negative results on an individual level. Additionally, there were likely vaccinated children and adolescents who were also infected, and therefore some underestimation of seroprevalence of the infected only cohort is. Including these children also as infected would increase the seroprevalence estimates due to infection rather than vaccination. Finally, despite the high participation rate, the use of venous blood sampling could have led to a selection bias.
Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04448717 Recruiting COVID-19: Longitudinal Study of Seroprevalence of SARS-CoV-2… Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
Results from scite Reference Check: We found no unreliable references.
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